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Test for submodel in Gibbs-Markov binary random sequence. (English) Zbl 0674.60094
Summary: The Gibbs-Markov random sequences (as studied in frame of statistical physics) are convenient as probability models for sequences of dependent binary data. Thus, the model is given by a system of interactions which may be understood and estimated as a vector parameter. Setting some of the interactions equal to zero, we obtain a submodel. A test for the submodel is derived in the present paper, and a numerical example with simulated data is included.
60K35 Interacting random processes; statistical mechanics type models; percolation theory
82B05 Classical equilibrium statistical mechanics (general)
60J99 Markov processes
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